AI to predict and improve peritoneal dialysis

  • Research type

    Research Study

  • Full title

    Use of Behavioural Artificial Intelligence to predict barriers and enablers to peritoneal dialysis

  • IRAS ID

    344467

  • Contact name

    Stuart Flint

  • Contact email

    sflint@scaledinsights.com

  • Duration of Study in the UK

    0 years, 11 months, 26 days

  • Research summary

    This research aims to find out if 1) an artificial intelligence solution that identifies personality characteristics can be used to predict a persons choice of kidney disease treatment (i.e. peritoneal or haemodialysis), and 2) whether messages designed for people who choose haemodialysis can be used to increase the likelihood that they would chose peritoneal dialysis instead.

    This study has two phases. In both phases, patients with kidney disease attending University Hospitals Birmingham NHS Foundation Trust will be invited to take part in the study.

    In phase 1, people who agree to take part, will be asked to identify the choice of dialysis treatment that they already have or would choose for kidney disease. They will also respond to open ended questions about treatment for kidney disease and lifestyle behaviour change that can help to manage kidney disease. Scaled Insights Behavioural Artificial Intelligence solution will be used to identify personality characteristics from the way people construct their sentences and these personality characteristics will be grouped and used to predict choice of dialysis.

    In phase 2, people who choose haemodialysis will be exposed to messages designed to support them to chose peritoneal dialysis instead.

  • REC name

    South West - Frenchay Research Ethics Committee

  • REC reference

    26/SW/0030

  • Date of REC Opinion

    19 Mar 2026

  • REC opinion

    Unfavourable Opinion